Data governance: how to implement it successfully?
Implementing solid data governance is a must if you want to make the most of your data assets. Knowing how to make the most of "data" capital requires setting up solid data governance.
In the age of digital business transformation, data is a goldmine for any organization that knows how to exploit it. With data, decision-making within companies is more precise and more impactful.
How can this be achieved?
We need to define the principles of corporate data governance (bodies, rules, confidentiality, etc.), to specify the type of data governance that will be adopted and define an implementation plan. Discover our best practices for developing an effective corporate data governance strategy.
Contents :
What is data governance? 🤔
Data governance represents the set of procedures, rules, standards, responsibilities and parameters that ensure that data is exploited efficiently, securely and effectively within the enterprise.
It should enable organizations to achieve their objectives. The company can also determine which information is sensitive, can be accessed by anyone or requires close monitoring in the data management strategy, etc.
Why implement a corporate data governance policy?
Companies are often faced with an ever-increasing volume of data. At the same time, the sources from which this information comes are increasingly vast (social networks, IoT, sensors, etc.).
Data exploitation has therefore become a necessity in a highly competitive and continually changing environment.
Today, companies can collect vast quantities of data, both internally and externally. Data has become the driving force behind customer relations, marketing projects and sales strategy. That's why data governance is essential for any company wishing to remain competitive in its field.
In addition to controlling and protecting sensitive data (data compliance), data governance must optimize the value of information, manage risks and reduce costs.
An enterprise data governance strategy is therefore essential for any company wishing to use data to develop and improve its analyses and operational processes.
What are the benefits of enterprise data governance?
Successfully implementing data governance means: making data reliable. It is then organized and accessible to all those who need it. The very essence of data governance is to bring all data together in a single system, and to provide employees with the tools they need to make all this data reliable, organized and exploitable.
Good data governance will enable you to work with better quality data.
Data governance has many benefits for organizations, including:
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improved data quality,
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more accurate decision-making,
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regulatory compliance,
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cost reduction and resource optimization,
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improved collaboration.
Better data quality
By implementing data policies, procedures or standards, your organization can ensure that your data is reliable, accurate and complete.
More accurate decision-making
Data governance provides decision-makers with accurate, up-to-date data to make more impactful decisions. This can help improve operational efficiency and drive business growth.
Regulatory compliance
Data governance helps you comply with data protection regulations and avoid financial penalties and negative reputational consequences.
Reduce costs and optimize your resources
By effectively managing data, organizations can reduce the costs associated with data maintenance, storage and management.
Better collaboration
Data governance facilitates collaboration between your organization's various stakeholders, by giving them easy access to relevant data.
Why implement a data governance strategy? 🤷♂️
An effective data governance strategy offers many benefits to organizations:
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through governance, the company obtains a uniform vision and common understanding of data.
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raw data is transformed into high-quality, comprehensive and consistent data,
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data governance enables all data to be mapped and presented in a better way. In addition, data governance makes it possible to link operational results with the data concerned,
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the company can define a single repository for the sales department, enabling a complete view of each customer,
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in terms of the RGPD, data management enables regulatory requirements to be met, as well as complying with other laws or directives such as those on health-related data or banking data,
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the introduction of governance improves data management by bringing a human dimension to a highly automated field. This translates into codes of conduct and best management practices,
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Thanks to data governance, companies can optimize their cash flow and boost performance. Indeed, it will be able to use its data wisely to maximize results.
Finally, by implementing readable and efficient data governance, your data will be reliable, easy to access and well documented.
It will be secure, compliant with laws and directives, and will respect the confidentiality of sensitive data.
How to set up effective data governance?
Best practice methodology
Awareness of data assets is nothing new. Today, however, certain circumstances call for stronger data governance:
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the adoption of the RGPD is forcing companies to make the necessary adaptations internally and vis-à-vis their customers,
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the acquisition of heterogeneous data volumes requires more robust and organized data governance,
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many companies are expressing their desire to be data-driven. To achieve this, they need to develop a more appropriate data governance strategy, and thus first become data-quality-driven.
Companies are therefore building their data governance around these 3 main axes.
Step 1: convince the management team and get their buy-in
About data governance....
To begin with, don't forget that the fundamental adage of data governance is to ask: what problems can be solved with data? From there, your argument will build itself.
However, the implementation of data governance is not an obvious process for everyone.
Some understand the importance of data, while for others, you'll have to argue, demonstrate and sell them the "product".
The "maneuver" consists in convincing people that data governance is essential from a strategic and business point of view.
This means talking to employees and explaining that certain data can help develop and support key projects.
It's also important to emphasize that data governance generally improves the operational efficiency of all departments within an organization.
Step 2: define your company's data strategy
Data governance strategies vary from company to company. They differ according to the size, nature and complexity of the company.
Typically, the development of a data governance strategy will be aligned with the business strategy, while identifying the problems to be solved. Next come the processes to be implemented to achieve the previously defined objectives. This involves defining data governance procedures, infrastructures and digital technologies, as well as training plans and skills management.
The development of a strategy also requires reflection on the type of data governance to be put in place:
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Should data remain under the control of the IT department?
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Is it possible to opt for alternative data governance?
In other words, any employee can take part in compiling data in compliance with standards and security. Each person can then help the company transform raw data into reliable data, document it and share it internally.
However, this model is only suitable for so-called non-sensitive data.
Step 3: Define the rules of data governance
Implementing data governance means establishing a set of standards, processes and rules to ensure that data is used effectively.
The rules put in place depend on the way the company operates.
However, certain regulatory texts must be compulsorily integrated into this set of standards. This applies in particular to the RGPD. You also need to think about establishing security and data recovery processes in the event of data loss or theft.
Once the rules and processes have been defined, they then need to be followed and respected by employees, and we know that it's sometimes difficult to stick with them over time.
Ensuring compliance of rules and processes is an imperative data governance. Only proper compliance with the rules will ensure secure use of data and more reliable updating of information. In fact, the company needs to control the evolution of rules and processes for modification and derogation over time.
Finally, data management is part of a complete ecosystem that needs to be fully managed. It's not just about data.
The set of processes and rules must be developed for the data itself, to manage the data storage spaces and to be applied when the data is used - this is what is akin to a data governance program.
Who is responsible for corporate data governance?
Defining roles is a crucial step. It's about choosing the people and functions responsible for implementing data governance. Here are a few key positions:
Chief data officer
The chief data officer is responsible for data governance strategy and the success of the policy. He or she must guarantee its implementation and adoption, and know how to adjust it if necessary.
Data owners
The job of data owner consists in collecting, storing and ensuring the relevance of data on a specific business or domain.
Data stewards
Data stewards are employees who operate at a more operational level. They guarantee data quality by checking datalakes. They also ensure compliance with policies and standards set by the various teams.
The data engineer
The data engineer's job is to develop and manage the databases needed to process the data in complete security.
Data quality managers
The role of data quality managers is to ensure that the various rules guaranteeing data quality and relevance are put in place.
Other data professions are also involved in data governance, such as data scientists, data analysts and data architects.
As you can see, setting up data governance calls on a wide range of data skills, and organizing all these players requires regular data committees, coaching, definition of job descriptions, etc.
Coordinate data activities and promote the value of data through governance
Once data governance has been defined, data managers will need to support data teams on a day-to-day basis. Internal communications must be put in place to:
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Disseminate the data culture within the company: this means defining a governance framework.
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Raise employee awareness of data issues through workshops, in particular by highlighting non-compliant data and presenting a solution as a governance program.
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Participate in the acculturation of new data-related professions, etc.
What are the obstacles to a data governance policy?
Data governance faces a number of obstacles to its effectiveness and implementation, despite its crucial nature.
Data diversity complicates data governance strategy
One of the main obstacles lies in the complexity and diversity of data. The growing influx of data, from a variety of sources and structured in disparate ways, makes the implementation of consistent governance policies and processes extremely complex.
Data protection and confidentiality
This is at the heart of any data governance strategy, and represents a constant challenge. Not only do we need to rigorously control access to data for the various stakeholders, but we also need to ensure that security best practices are respected at all times. Data breaches and security failures are major risks, which can not only undermine user confidence, but also lead to serious legal and financial consequences.
The cost of data governance
Implementing an effective data governance policy also comes at a cost. First and foremost, it requires substantial investment in terms of technology, as well as in-house training of staff to ensure compliance with the best practices outlined above. These resources are not necessarily accessible to all companies, especially smaller ones.
Changing regulations
Another challenge lies in the evolution of regulations, particularly those relating to the protection of personal or sensitive data, such as the RGPD law, which continues to evolve over time. These regular changes require constant adaptation of governance practices, which can be difficult to maintain in terms of compliance.
Collaboration and data sharing between different companies
In addition, data governance can sometimes hinder collaboration and data sharing between different companies/organizations, as in the case of new policies under personal data regulations. Strict policies can make it difficult to share data, which can limit innovation and partnership opportunities for certain companies in certain sectors.
Which tool should you choose for your data governance?
Today, there are a number of data governance solutions that enable data to be exploited in a comprehensible, secure and reliable way. Depending on the big data tool you choose, you'll find that there are significant differences when it comes to using them. Some tools require technical or programming knowledge, while others are no-code.
The Tale of Data solution enables you to adopt the right approach to data governance, in no-code. It enables you to understand your different types of data, identify where they are and how they can be exploited.
To give you an idea of the solution's capabilities, Tale of Data connects to different data sources (NoSQL, relational databases, file storage, etc.) to assemble the data.
The data is cleansed: deduplication, merging and transformation are the prerequisites for a successful project.
Once this stage has been completed, the solution prepares and delivers the data in an easily usable format.
Why use Tale of Data for cloud data governance?
Its ability to let you read, write to and from any type of structured file (CSV, Excel, JSON, XML, etc.), whether stored in-house or in the cloud.
Tale of Data supports companies of all sizes through five essential stages: discovering, auditing, structuring, enriching and exploiting data. The software's various functionalities will give you greater control over your data, and therefore improved internal performance.
Conclusion
In conclusion, by opting for solid data governance with Tale of Data, you can be sure of achieving your objectives and obtaining a common, consistent understanding of your data.
Tale of Data can help you understand your data, because understanding data is the key to :
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maximize the benefits that data can bring to your business (optimizing processes, communication campaigns, customer knowledge, improving service quality and security)
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minimize your risks (fraud, detection of anomalies, loss of customers, etc.)
👉 Implementing data governance means collecting data that adds value to your business.
Enhancing your data with Open Data
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